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Development and Validation of TACE Refractoriness-Related Diagnostic and Prognostic Scores and Characterization of Tumor Microenvironment Infiltration in Hepatocellular Carcinoma

BACKGROUND: Transcatheter arterial chemoembolization LIHC, Liver hepatocellular carcinoma; (TACE) is a valid therapeutic method for hepatocellular carcinoma (HCC). However, many patients respond poorly to TACE, thus leading to an adverse outcome. Therefore, finding new biomarkers for forecasting TAC...

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Autores principales: He, Qifan, Yang, Jian, Jin, Yonghai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9043752/
https://www.ncbi.nlm.nih.gov/pubmed/35493518
http://dx.doi.org/10.3389/fimmu.2022.869993
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author He, Qifan
Yang, Jian
Jin, Yonghai
author_facet He, Qifan
Yang, Jian
Jin, Yonghai
author_sort He, Qifan
collection PubMed
description BACKGROUND: Transcatheter arterial chemoembolization LIHC, Liver hepatocellular carcinoma; (TACE) is a valid therapeutic method for hepatocellular carcinoma (HCC). However, many patients respond poorly to TACE, thus leading to an adverse outcome. Therefore, finding new biomarkers for forecasting TACE refractoriness occurrence and prognosis becomes one of the current research priorities in the field of HCC treatment. MATERIALS AND METHODS: Based on microarray datasets and a high-throughput sequencing dataset, the TACE refractoriness–related genes (TRGs) were identified by differential expression analysis. LASSO and Cox regression were applied to construct TACE refractoriness diagnostic score (TRD score) and prognostic score (TRP score) and validated their accuracy in external datasets. Functional correlation of TRP score was analyzed by gene set variation analysis and Gene Ontology. CIBERSORT and IMMUNCELL AI algorithms were performed to understand the correlation between the two scores and immune activity. We further carried out the efficacy analysis of immunotherapy and targeted drugs in the different TRP score groups. Furthermore, a nomogram was built by integrating various independent prognostic factors and validated its effectiveness in different datasets. RESULTS: We identified 487 TRGs combined with GSE104580 and TCGA datasets. Then four novel TRGs (TTK, EPO, SLC7A11, and PON1) were screened out to construct TRD score and TRP score models, and both two scores had good predictive ability in external datasets. Tumors with high TRP score show an immunosuppressive phenotype with more infiltrations of regulatory T cells and macrophages. Immunotherapy and chemotherapy response evaluation revealed patients with a high TRP score demonstrated well reactions to immune checkpoint inhibitors (ICIs) and sorafenib. TRP score, TNM stage, and cancer type were brought into the combined nomogram with optimum prediction. CONCLUSIONS: Our research provided dependable and simplified methods for patients with HCC to assess tumors’ susceptibility to TACE refractoriness and prognosis and guide patients’ clinical therapy choices.
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spelling pubmed-90437522022-04-28 Development and Validation of TACE Refractoriness-Related Diagnostic and Prognostic Scores and Characterization of Tumor Microenvironment Infiltration in Hepatocellular Carcinoma He, Qifan Yang, Jian Jin, Yonghai Front Immunol Immunology BACKGROUND: Transcatheter arterial chemoembolization LIHC, Liver hepatocellular carcinoma; (TACE) is a valid therapeutic method for hepatocellular carcinoma (HCC). However, many patients respond poorly to TACE, thus leading to an adverse outcome. Therefore, finding new biomarkers for forecasting TACE refractoriness occurrence and prognosis becomes one of the current research priorities in the field of HCC treatment. MATERIALS AND METHODS: Based on microarray datasets and a high-throughput sequencing dataset, the TACE refractoriness–related genes (TRGs) were identified by differential expression analysis. LASSO and Cox regression were applied to construct TACE refractoriness diagnostic score (TRD score) and prognostic score (TRP score) and validated their accuracy in external datasets. Functional correlation of TRP score was analyzed by gene set variation analysis and Gene Ontology. CIBERSORT and IMMUNCELL AI algorithms were performed to understand the correlation between the two scores and immune activity. We further carried out the efficacy analysis of immunotherapy and targeted drugs in the different TRP score groups. Furthermore, a nomogram was built by integrating various independent prognostic factors and validated its effectiveness in different datasets. RESULTS: We identified 487 TRGs combined with GSE104580 and TCGA datasets. Then four novel TRGs (TTK, EPO, SLC7A11, and PON1) were screened out to construct TRD score and TRP score models, and both two scores had good predictive ability in external datasets. Tumors with high TRP score show an immunosuppressive phenotype with more infiltrations of regulatory T cells and macrophages. Immunotherapy and chemotherapy response evaluation revealed patients with a high TRP score demonstrated well reactions to immune checkpoint inhibitors (ICIs) and sorafenib. TRP score, TNM stage, and cancer type were brought into the combined nomogram with optimum prediction. CONCLUSIONS: Our research provided dependable and simplified methods for patients with HCC to assess tumors’ susceptibility to TACE refractoriness and prognosis and guide patients’ clinical therapy choices. Frontiers Media S.A. 2022-04-13 /pmc/articles/PMC9043752/ /pubmed/35493518 http://dx.doi.org/10.3389/fimmu.2022.869993 Text en Copyright © 2022 He, Yang and Jin https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
He, Qifan
Yang, Jian
Jin, Yonghai
Development and Validation of TACE Refractoriness-Related Diagnostic and Prognostic Scores and Characterization of Tumor Microenvironment Infiltration in Hepatocellular Carcinoma
title Development and Validation of TACE Refractoriness-Related Diagnostic and Prognostic Scores and Characterization of Tumor Microenvironment Infiltration in Hepatocellular Carcinoma
title_full Development and Validation of TACE Refractoriness-Related Diagnostic and Prognostic Scores and Characterization of Tumor Microenvironment Infiltration in Hepatocellular Carcinoma
title_fullStr Development and Validation of TACE Refractoriness-Related Diagnostic and Prognostic Scores and Characterization of Tumor Microenvironment Infiltration in Hepatocellular Carcinoma
title_full_unstemmed Development and Validation of TACE Refractoriness-Related Diagnostic and Prognostic Scores and Characterization of Tumor Microenvironment Infiltration in Hepatocellular Carcinoma
title_short Development and Validation of TACE Refractoriness-Related Diagnostic and Prognostic Scores and Characterization of Tumor Microenvironment Infiltration in Hepatocellular Carcinoma
title_sort development and validation of tace refractoriness-related diagnostic and prognostic scores and characterization of tumor microenvironment infiltration in hepatocellular carcinoma
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9043752/
https://www.ncbi.nlm.nih.gov/pubmed/35493518
http://dx.doi.org/10.3389/fimmu.2022.869993
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